code: def _run_augment(self, augment_config, image, bboxes):
      self.base_config["dataset"]["data_augmentation"] = augment_config
  
      bboxes_tf = tf.placeholder(tf.int32, shape=bboxes.shape)
      image_tf = tf.placeholder(tf.int32, shape=image.shape)
  
      model = ObjectDetectionDataset(self.base_config)
      image_aug, bboxes_aug, applied_data_augmentation = model._augment(
          image_tf, bboxes_tf
      )
  
      with self.test_session() as sess:
          image_aug, bboxes_aug, applied_data_augmentation = sess.run(
              [image_aug, bboxes_aug, applied_data_augmentation],
              feed_dict={
                  bboxes_tf: bboxes,
                  image_tf: image,
              },
          )
          return image_aug, bboxes_aug, applied_data_augmentation
  
file_path: luminoth/luminoth/datasets/object_detection_dataset_test.py
imports: import tensorflow
  import numpy
  from easydict import EasyDict
  from luminoth.datasets.object_detection_dataset import ObjectDetectionDataset
label_desc: Use image node_id 2 for calling the ObjectDetectionDatasetTest obj's underlying member method code with example usage: obj._run_augment(augment_config, image, bboxes) and returns: image_aug,  bboxes_aug,  applied_data_augmentation